Edge Technology aims at making Internet Of Things (IOT) with 100 thousands of sensors in next decade, with the increased usage and manipulation of large data it becomes important to get used to this technology which refers to computing on sensor itself. 2019 is predicted as the year of edge technology and will remain so in the coming years.
In a variety of situations edge computing is deployed. One is when IOT devices is centrally connected to cloud due to poor connectivity of devices. By the year 2020, there will be approximately 1.5 GB worth of data is generated per day. With many devices connected to the internet and generating data, its not possible for cloud alone to handle this huge data all by itself.
Edge can relate to data processing as well as local processing of the real time data. The various edge components that can be counted upon are Data processing, Rule Engine, Local Database.
Why Edge Computing?
- This technology increases the efficient usage of bandwidth by analysing the data at edges itself unlike the cloud which requires transfer of data from the IOT requiring large bandwidth, making it useful to be used in remote location with minimum cost.
- It allows smart applications and devices to respond to data almost at the same time which is important in terms of business ad self driving cars.
- It has the ability to process data without even putting on a public cloud, this ensures full security.
- Data might get corrupt while on an extended network thus affecting the data reliability for the industries to use.
- Edge computation of data provides a limitation to the use of cloud.
Edge vs Fog Computing:
Edge is more specific towards computational processes for the edge devices. So, fog includes edge computing, but would also include the network for the processed data to its final destination.
Real Life Application Of Edge Technology:
- Autonomous Vehicles –
GE Digital partner, Intel, estimates that autonomous cars, with hundreds of on-vehicle sensors, will generate 40 TB of data for every eight hours of driving. Therefore, wheels—edge computing plays a dominant role. Sending all the data to cloud is unsafe and impractical. The car immediately response to the events which has valuable data when coupled into digital twin and performance of other cars of its class.
- Fleet Management –
Let’s example considering a trucking company, the main goal is to combine and send data from multiple operational data points like wheels, brakes, battery , etc to the cloud. Health key operational components are analysed by the cloud. Thus,essentially a fleet management solution encourages the vehicle to lower the cost.
5 Key Benefits Of Edge Computing:
- Faster response time.
- Security and Compliance.
- Cost-effective Solution.
- Reliable Operation With Intermittent Connectivity.
Edge Cloud Computing Services:
- IOT (Internet Of Things)
- Health Care
- Smart City
- Intelligent Transportation
- Enterprise Security
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- Serverless Computing
- Cloud Computing
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- Introduction to Parallel Computing
- Anatomy of Cloud Computing
- Energy Efficiency in Cloud Computing
- Licenses and their management in Cloud Computing
- MPI - Distributed Computing made easy
- Virtualization In Cloud Computing and Types
- Load balancing in Cloud Computing
- Cloud Computing | Characteristics of Virtualization
- Cloud computing Research challenges
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